Detection of spread spectrum signals

ABSTRACT

A spread spectrum signal detection system comprising two spatially separated receivers, a correlator, such as a time integrating correlator employing acousto-optic cells, which is connected to the outputs from the two receivers to produce a signal representative of the cross correlation function of the two spread spectrum signals, a filter arranged to transmit only the central portion of the cross correlation function and a signal processor to produce the cross spectral density and thereby determine the presence of the spread spectrum signal. The direction of arrival of the spread spectrum signal can be determined by measurement of the angle of the phase slope of the cross spectral density. The acousto-optic cells can be Bragg cells. The output signal from one of the receivers can be applied to a first Bragg cell arranged to point modulate light from a laser light source, the output then being transmitted through a beam expander to a second Bragg cell to which the output signal from the second receiver can be applied, the output from the second Bragg cell then being detected by a photo-detector array. The output from the second Bragg cell can be spatially filtered by providing adjustable imaging optics arranged such that only light corresponding to the central portion of the cross correlation function is transmitted. The processor can be arranged to demodulate the signals to produce data corresponding to the central portion of the cross correlation function and to Fourier transform the data to produce the cross spectral density.

The invention relates to the detection of low power spread spectrumsignals as used, for example, in many modern radars and in particularthough not exclusively to direction finders using the cross correlationof signals received from two spatially separated receivers.

Many modern radars use spread spectrum techniques. This enables them toachieve good range resolution with low power outputs, and it also givesthem LPI (Low Probability of Intercept) properties. The radar receiver,with its matched filter, can make use of the full processing gainavailable from a pulse of CW signal with large time-bandwidth product.An ESM receiver can not normally take advantage of this potentialprocessing gain, and is additionally hampered by having to have arelatively wide bandwidth with a consequent noise penalty.

If a system attempting to detect and locate spread spectrum signals usestwo spatially separated receivers and cross correlates the two receivedsignals, it can achieve much of the processing gain available to thematched filter receiver. The two signals will contain both antenna noiseand internal receiver noise. The internal noise in the two receiverswill be independent and will not correlate. Much of the two sets ofantenna noise comes from the same sources. However, if these sources arespatially distributed then the signals from these sources arrive at thetwo antennas with a distribution of time delays, and the antenna noisesignals are effectively uncorrelated. Any fixed signal source (emittinga spread spectrum signal) will, however, emit a signal that will bepresent in both receiver inputs with a single fixed time delay. Thecross correlation function of the two receiver outputs will contain theautocorrelation function of the signal coming from any fixed source,shifted along the time axis according to the time difference of arrivalat the antennas. It will also contain two cross correlations of thesignal in one receiver with the noise in the other, and the crosscorrelation of the two sets of noise. For large input signal to noiseratios the noise-noise cross correlation will be insignificant and thecorrelator output will effectively contain the signal autocorrelationfunction plus the two signal-noise cross correlations.

However, we are generally more interested in the case where the inputsignal to noise ratio is small. The noise-noise cross correlation willthen dominate and the system will perform much worse than the matchedfilter, unless we can find some other way of rejecting a significantportion of the noise. This is possible. If the noise signals in the tworeceivers are indeed uncorrelated, then the signal-noise and noise-noisecross correlations will simply be noise signals spread, more or lessuniformly, over the full length of the cross correlation function.However, the signal autocorrelation function will, for a spread spectrumsignal be concentrated in the centre. If we take just the centralportion of the cross correlation function, therefore, we can reject mostof the noise energy present. This does not help us if we are concernedwith making measurements, such as threshold detection, on the timedomain cross correlation function.

It should also be noted that, because it has no a-priori timinginformation, the ESM system cannot integrate over several pulses in theway that the radar can.

If we wish to direction find on a fixed signal source, we can obtain thetime difference of arrival at the antennas by direct measurements on thecross correlation function. However the resolution of this is limited bythe width of the main lobe of the signal auto correlation function,which is approximately the inverse of the signal bandwidth. For example,a system using a baseline of 50 m to direction find on a signal ofbandwidth 10 MHz would have a bearing resolution of about 34° at best.Such direct measurement of the position of the autocorrelation functionusing threshold detection is, of course, very crude and fails to makeuse of the phase information present in the cross correlation function.

The object of the invention is to provide a cross correlation receiverdetection system which is capable of providing improved detection andsubstantially greater positional accuracy than hitherto possible.

The invention provides a spread spectrum signal detection systemcomprising:

two spatially separated receivers for detecting the spread spectrumsignal;

a correlator having first and second inputs connected to the outputsfrom the two receivers to produce at an output thereof a signalrepresentative of the cross correlation function of the spread spectrumsignals received by the two receivers;

a filter having an input connected to the output of the correlatorarranged to transmit to an output thereof only the central portion ofthe cross correlation function; and

a signal processor connected to the output from the filter to producethe cross spectral density and thereby determine the presence of thespread spectrum signal.

In the preferred arrangement of the invention the direction of arrivalof the spread spectrum signal at the detection system can be determinedby measurement of the angle of the phase slope of the cross spectraldensity.

In the preferred arrangement the correlator is a time integratingcorrelator employing acousto-optic cells. The acousto-optic cells arepreferably Bragg cells. In a convenient arrangement the output signalfrom one of the receivers is applied to a first Bragg cell arranged topoint modulate light from a laser light source, the modulated lightoutput from the first Bragg cell is then transmitted through a beamexpander to a second Bragg cell to which the output signal from thesecond receiver is applied, the modulated output light from the secondBragg cell then being detected by a photo-detector array.

Preferably, in order to reduce the computational demands on the system,the modulated light output from the second Bragg cell is spatiallyfiltered by providing imaging optics arranged such that only lightcorresponding to the central portion of the cross correlation functionis transmitted. Advantageously there is provided means to adjust theimaging optics to ensure that only the light corresponding to thecentral portion of the cross correlation function is transmitted throughthe spatial filter.

The output signals from each diode of the photo-diode array arepreferably connected to a digital signal processor arranged firstly todemodulate the signals to produce data corresponding to the centralportion of the cross correlation function and secondly to Fouriertransform the data to produce the cross spectral density.

The Fourier transform is conveniently done by means of a fast Fouriertransformer (FFT).

The detection system is advantageously arranged such that a peakmeasurement in the cross spectral density leads to an output signalindicating presence of a target signal.

For target bearing information the DSP is arranged such that the angleof the phase slope of the cross spectral data is made. Preferably aleast squares method is applied to determine the phase slope.

The invention will now be described by way of example with reference tothe accompanying Drawings of which:

FIG. 1 is a block diagram of a two receiver correlation signal detectionand direction finder;

FIG. 2 shows a practical time domain correlator using Bragg cells;

FIG. 3 shows an autocorrelation function of one receiver output;

FIG. 4 shows the cross correlation of the outputs from the tworeceivers;

FIGS. 5 and 6 show the effect of zooming in on the centres of thefunctions shown in FIGS. 3 and 4 respectively;

FIG. 7 shows the power spectral density corresponding to theautocorrelation function shown in FIG. 3;

FIG. 8 shows the time domain filtered cross spectral density obtainedfrom the FIG. 6 data; and

FIG. 9 shows the phase slope of the FIG. 8 data as used to determine thedirection of arrival of a received signal.

FIG. 1 illustrates a direction finder in which a weak spread spectrumsignal 10 arrives at two detectors from an angle 0. The detectorscomprise antennas 11, 12, spatially separated by a distance d, andrespective low noise RF amplifiers 13, 14. The output signals from theamplifiers 13, 14 are mixed with the output signal from a stable lownoise oscillator 15 in mixers 16, 17 and the output signals from themixers are cross-correlated in cross correlator 18. The output signalfrom the cross correlator 18 is then connected to a digital signalprocessor (DSP) 19. When the cross correlation of the outputs of the 2receivers is formed, the signal-signal cross correlation, for a spreadspectrum signal 10, is concentrated almost totally in small regions inthe centre of the cross correlation function while noise terms arespread out over the full range of the total cross correlation function.Once the spread spectrum signal has been detected the angle of arrival 0can be determined if the time difference of arrival at the two receiverscan be obtained. This time difference is manifested in the crosscorrelation function as a shift in the position of the correlation peakfrom the centre. Unfortunately this shift generally cannot be measuredwith sufficient accuracy to be useful.

A time shift in the time domain cross correlation function is equivalentto a linear phase slope in the frequency domain cross spectral density.Thus, if the complex cross spectral density is stored digitally thenthis phase slope can be extracted to give the angle of arrival 0. First,the part of the cross spectral density containing the signal must beestablished. This is done by threshold detection of the magnitude.Second, the phase terms need to be unwrapped by means of an appropriatealgorithm which adds or subtracts 2 pi as appropriate when a suddenphase change is detected between successive stored points. The inventorhas shown that the unwrapping algorithm can fail, particularly for weaksignals, if the cross spectral density is not time domain filtered.

To sample the signals from the two receivers and perform the necessarycross correlations digitally in real time may not be feasible,especially if we wish to design a system with large channel bandwidthsand long sample lengths. For example: a channel bandwidth of 1 GHz and asample length of 50 μs would require analogue to digital conversion at asampling frequency of 2 GHz and data sets of 50,000 points.

Acousto-optic correlators may provide the answer to the problem offorming the initial cross correlation function. The fact that we thenonly want to sample a relatively small centre portion of the crosscorrelation function is very convenient since this means that the numberof data points we have to extract for further processing is very muchreduced.

FIG. 2 shows a time integrating correlator implementation for use as thecross correlator 18 in FIG. 1. This arrangement of correlator isdescribed by Vanderlugt "Optical Signal Processing", Wiley Interscience,1992 pp520-526. A laser light source 20 is shown incident on a firstBragg cell 21, driven by a first (S₁ (t)) of the two signals to becorrelated. This produces point modulation of the laser light which isexpanded by a beam expander 22 to illuminate a second Bragg cell 23driven by the second signal S₂ (t). Both signals S₁ (t) and S₂ (t) havea bias 24, 25 added before connection to the respective Bragg cells. Inaddition the second signal S₂ (t) is modulated by an oscillator signalof frequency W_(c) in a mixer 26. The modulated light from the secondBragg cell 23 is then transmitted through a spatial filter 27, situatedbetween converging lenses 28, 29, to a photodetector array 210. Theoutput signals from the array 210 are then connected to a DSP 211. Inthe DSP 211 the Fourier transform, obtained by a fast Fourier transformprocessor (FFT), of the truncated cross correlation function is used toproduce the time domain filtered cross spectral density. A least squaresor other suitable technique is then used to determine the phase slope ofthe cross spectral density and hence the direction of arrival of thedetected signal.

Vanderlugt shows that the time integrated light intensity at the planeof the photodetector array contains a spatially invariant term which isproportional to the integration time and the cross correlation functionof the two input signals imposed as double sideband suppressed carriermodulation of a spatial carrier. This correlator is ideal for therequired process of windowing the centre portion of the crosscorrelation function. The spatial dimensions of the cross correlationfunction are controlled by adjustment of the imaging optics so that therequired centre portion falls on the photodetector array. The spatialfunction is then sampled by the array and all further processingperformed digitally, including demodulating the spatial signal torecover the correlation function from the carrier.

This arrangement takes advantage of the speed of optical signalprocessing for the correlation and the flexibility of digital signalprocessing once the sets of data points has been reduced to manageablenumbers.

In the proposed implementation of the FIG. 2 arrangement a Fairchild2048 element CCD linescan camera is used, controlled by and deliveringits data to, a TMS320C30 based framegrabber and digital signalprocessing board mounted in a host PC.

In this arrangement the limited dynamic range of the acousto-optic Braggcells need not be a problem. Where the system is intended to look forsignals below the noise level, the system would be set up with RF and IFgains such that the standard deviation of the noise is approximately onethird of the amplitude range of the correlator inputs. Short high powerpulses will be severely clipped. This goes some way towards eliminatingthe non LPI pulses that would be detected by a conventional system,although they would of course be better excluded by the use of notchfilters to block known signals.

Simulation of this system has shown that it should be highly effectiveagainst LPI radars. By use of the time domain filtered cross spectraldensity, such a system should, in addition to detecting spread spectrumsignals at power levels well below the sensitivities of current ESMsystems, be able to direction find on such signals.

One type of radar having LPI properties is the FMCW radar, an example ofwhich is the PILOT navigation radar which operates at about 9 GHz. Thisis described in Beasley PDL and Stove AG: "PILOT--an example of advancedFMCW techniques", IEE Colloq, an "High time-bandwidth product waveformsin radar and sonar", IEE Digest No 093, 1991. PILOT employs a sawtoothfrequency sweep of 50 MHz with a time period of 1 ms within a bandwidthof 1 GHz. If a cross correlating detection system uses a sample time of50 μs then it can only `see` a frequency sweep of 2.5 MHz. Using a timedomain correlator as proposed in this invention, it can be shown thatthe time domain filtered Cross Spectral Density gives a significantlyhigher output signal to noise ratio than the cross correlation function.Hence use of the cross spectral density gives increased detectability ofthe FMCW signal at lower powers. In addition, detection improves withlonger integration time.

The inventor has shown that the main peak of the autocorrelationfunction of an LPI radar pulse is very narrow, the time shift betweenthe two inputs to the receivers is also small, and the noise in thecross correlation function is spread across the whole width of thefunction. Therefore much of the noise can be eliminated by simplyrejecting all but the centre portion of the cross correlation functionby use of the spatial filter 27. Then, taking the Fourier transform ofthis windowed function produces the time domain filtered cross spectraldensity. It has further been shown that for short samples or systems inwhich the noise bandwidth is much greater than the bandwidth of thesignal within the sample, the time domain filtered cross spectraldensity can have a significantly higher signal to noise ratio than thecross correlation function. Simulation has demonstrated that measurementof the phase slope of the relevant part of the time domain filteredcross spectral density can give accurate direction finding. Thisdirection finding is especially accurate if a number of successive crosscorrelation functions are coherently summed, simulating the effect of along sample length, before formation of the time domain filtered crossspectral density.

If a radar uses long spread spectrum pulses, then an ESM system with noprocessing gain will have no range advantage, even if it uses achannellised receiver with a large number of narrow channels. A crystalvideo receiver will be much more sensitive but will still not achieve auseful range advantage over an LPI radar, even when it has a-prioriknowledge of the pulse length, allowing it to optimise the videobandwith. It has been shown that a dual receiver cross correlating ESMsystem, which requires virtually no a-priori information, will alwaysperform significantly better than a crystal video receiver. If the ESMsystem noise bandwidth is more than 12 times greater than the bandwidthof the signal contained within a sample, then use of the time domainfiltered cross spectral density can offer greater sensitivity. Use ofthis cross spectral density also enables discrimination between signalsof different frequencies within the same RF channel and extremelyaccurate direction finding.

A simulation model has been developed to illustrate the invention.

The model parameters were: a receiver noise bandwidth of 80 MHz, an FMCWsignal sweeping up through a bandwidth of 10 MHz in 0.5 ms, a receiveroutput signal to noise ratio of --13 dB, and an antenna separation of 50m. Ten cross correlations were performed on successive 50 μs samples andsummed. Although the resulting cross correlation function has a very lowsignal to noise ratio, when viewed in the time domain, direction findingusing the phase slope of the time domain filtered CSD gave a directionof arrival measurement, on a source at 30° from the two element arraybroadside, with an error of less than 0.5°. The following Figuresdemonstrate the process.

FIG. 3 shows the autocorrelation function of one of the receiver outputsfor comparison with the cross correlation function. This autocorrelationfunction is clearly dominated by the very large noise autocorrelationpeak 30.

FIG. 4 shows the cross correlation of the two receiver outputs, on thesame scale as FIG. 3. The components 40 due to the noise are now spreadover the full width of the function.

FIGS. 5 and 6 show the result of zooming in on the centres of theautocorrelation function shown in FIG. 3 and the cross correlationfunction shown in FIG. 4 by a factor of 64. 50 is the autocorrelationpeak. While it is apparent that the central lobe 60 of the crosscorrelation function does contain a time shift, estimation of this shiftdirectly by threshold detection would give very poor results.

FIG. 7 shows the power spectral density 70 obtained simply by taking theFourier transform of the autocorrelation function shown in FIG. 3. Thisis basically the same as a straight forward FFT analysis of one receiveroutput. It is clearly not very useful.

FIG. 8 shows the magnitude of the time domain filtered cross spectraldensity obtained by taking the fast Fourier transform (FFT) of thetruncated cross correlation function shown in FIG. 6. The 10 MHzbandwidth signal 80 now shows up very clearly.

FIG. 9 shows the unwrapped phase 90 of the time domain filtered CSD,with a straight line 91 fitted to the section within the signal band.From the slope of this straight line we can calculate the time shift inthe cross correlation function and hence the direction of arrival of thesignal. The actual time delay between the two signals in the modelcorrespond to a direction of arrival of 30°. The direction of arrivalcalculated from the slope of the straight line in FIG. 9 was 30.3°.

Although other types of acousto-optic correlator may be used, such as aspace integrating correlator or a joint transform correlator, the timeintegrating correlator described is particularly beneficial for realtime data processing using only the centre portion of the crosscorrelation function.

We claim:
 1. A spread spectrum signal detection system comprising:a) twospatially separated receivers for detecting the spread spectrum signal;b) a correlator having first and second inputs connected to the outputsfrom the two receivers to produce at an output thereof a signalrepresentative of the cross correlation function of the spread spectrumsignals received by the two receivers; c) a filter having an inputconnected to the output of the correlator arranged to transmit to anoutput thereof only the central portion of the cross correlationfunction; and d) a signal processor connected to the output from thefilter to produce the cross spectral density and thereby determine thepresence of the spread spectrum signal.
 2. A spread spectrum signaldetection system as claimed in claim 1 wherein the direction of arrivalof the spread spectrum signal at the detection system is determined bymeasurement of the angle of the phase slope of the cross spectraldensity.
 3. A spread spectrum signal detection system as claimed inclaim 1 wherein the correlator is a time integrating correlatoremploying acousto-optic cells.
 4. A spread spectrum signal detectionsystem as claimed in claim 3 wherein the acousto-optic cells are Braggcells.
 5. A spread spectrum signal detection system as claimed in claim4 wherein the output signal from one of the receivers is applied to afirst Bragg cell arranged to point modulate light from a laser lightsource, the modulated light output from the first Bragg cell is thentransmitted through a beam expander to a second Bragg cell to which theoutput signal from the second receiver is applied, the modulated outputlight from the second Bragg cell then being detected by a photo-detectorarray.
 6. A spread spectrum signal detection system as claimed in claim5 the modulated light output from the second Bragg cell is spatiallyfiltered by providing imaging optics arranged such that only lightcorresponding to the central portion of the cross correlation functionis transmitted in order to reduce the computational demands on thesystem.
 7. A spread spectrum signal detection system as claimed in claim6 wherein there is provided means to adjust the imaging optics to ensurethat only the light corresponding to the central portion of the crosscorrelation function is transmitted through the spatial filter.
 8. Aspread spectrum signal detection system as claimed in claim 5 whereinthe output signals from each detector of the photo-detector array areconnected to a digital signal processor (DSP) arranged firstly todemodulate the signals to produce data corresponding to the centralportion of the cross correlation function and secondly to Fouriertransform the data to produce the cross spectral density.
 9. A spreadspectrum signal detection system as claimed in claim 8 wherein theFourier transform is done by means of a fast Fourier transformer (FFT).10. A spread spectrum signal detection system as claimed in claim 1wherein the detection system is arranged such that a peak measurement inthe cross spectral density leads to an output signal indicating presenceof a target signal.
 11. A spread spectrum signal detection system asclaimed in claim 8 wherein for target bearing information the DSP isarranged such that the angle of the phase slope of the cross spectraldata is determined.
 12. A spread spectrum signal detection system asclaimed in claim 11 wherein a least squares method is applied todetermine the phase slope.
 13. A method of detecting a spread spectrumsignal, said method comprising the steps of:receiving a spread spectrumsignal to be detected with two spatially separated receivers andproviding respective receiver outputs; correlating the receiver outputsand providing a signal representative of the cross correlation functionof the spread spectrum signal received by the two receivers; filteringthe signal representative of the cross corrrelation function andproviding an output comprised of only the central portion of the crosscorrelation function; and using a signal processor responsive to thecentral portion output to produce a cross spectral density and therebyprovide an indication of the presence of said spread spectrum signal.14. A method of detecting a spread spectrum signal in accordance withclaim 13, including the further step of measuring an angle of the phaseslope of the cross spectral density to determine the direction ofarrival of the spread spectrum signal.